There are different types of three-dimensional visualization. Some visualizations offer a depth image, or 2.5 D image. These techniques do not make it possible to recover all the three-dimensional voxels (“volumetric pixels”), they are founded on the stereoscopic techniques linked to the optimization of a difference of progression of the optical or electromagnetic ray between the different points of two images; this difference of progression can be calculated if the objects are situated at a short range from the imaging system. The identification is therefore limited to short distances.
Some imaging techniques require a laser beam or light scanning over the scene, and a sequence of measurements gives a 3D cloud of points. Several scans with different viewing angles are necessary to obtain three-dimensional information but the relative motion of the carrier containing the scanning system produces a distortion from point cloud to point cloud, the realignment is complex and degrades the resolution and the identification.
The so-called silhouette techniques, with silhouettes obtained from multiple views give an outer envelope with little detail. If the objects contain a shadow zone or if an object is located in the shadow of another object, a large part of the envelope is lost, therefore the identification and the discrimination of the two objects is not feasible.
The Spin Image type technologies require databases and cannot be applied for objects concealed in complex scenes without a priori knowledge.
The voxel grouping techniques associated with isodensity surface reconstruction make it possible to obtain the outer surface of the objects but eliminate the internal information contained in the object.
The three-dimensional reconstruction techniques linked to a knowledge base optimization and to the extraction of weak signals and an example of which is presented in document “Method for the three-dimensional synthetic reconstruction of objects exposed to an electromagnetic and/or elastic wave” (EP 2 929 421 or U.S. Pat. No. 8,345,960), require databases and for them to be optimized in order to produce the best possible three-dimensional reconstruction. The knowledge bases often represent the objects only by a set of external three-dimensional surfaces which can be modeled by facets. The transparent structures (windows, etc.) are poorly taken into account, which greatly impairs the complete display of the object in 3D. These techniques are also dependent on the availability of the knowledge bases.
The MIP (Maximum Intensity Projection) technique allows for the 2D visualization of three-dimensional data. This technique projects the voxels onto a projection plane; the voxels are determined by the rays meeting the projection plane at the point of observation with an imposed intensity threshold. The 2D results do not make it possible to obtain a value for the depth and the distances. To create an illusion of rotation and a concept of depth and thus enhance the 3D rendering, several projection planes are produced with successive observation angles.
The voxel intensity rendering techniques allow for a noisy three-dimensional visualization, which reduces the discrimination between different contiguous of the observed scene.
The 3D clouds of points obtained directly by a Cartesian positioning of the voxels allow only a weak discrimination and provide artefacts associated with the false alarms.
The surface completion techniques, an example of which is presented in the document “Method for 3D reconstruction of an object of a scene” (US2013/0100131), make it possible to fill the incomplete zones by three-dimensional surface generation to obtain a set of completed data of the object, without recourse to an external database. They thus give a complete external surface of the object without surface discontinuity; the internal data situated behind transparent objects (windows for example) are not reconstructed and are eliminated from the identification process. A process for discriminating two close objects is more difficult to achieve, because the generation of surfaces can be mathematically complex.